An Efficient and Generalized approach for Content Based Image Retrieval in MatLab.
Author(s) -
Shriram K. Vasudevan,
P. L. K. Priyadarsini,
V Subashri
Publication year - 2012
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2012.04.06
Subject(s) - content based image retrieval , content (measure theory) , matlab , computer science , image (mathematics) , image retrieval , computer vision , artificial intelligence , information retrieval , mathematics , programming language , mathematical analysis
There is a serious flaw in existing image search engines, since they basically work under the influence of keywords. Retrieving images based on the keywords is not only inappropriate, but also time consuming. Content Based Image Retrieval (CBIR) is still a research area, which aims to retrieve images based on the content of the query image. In this paper we have proposed a CBIR based image retrieval system, which analyses innate properties of an image such as, the color, texture and the entropy factor, for efficient and meaningful image retrieval. The initial step is to retrieve images based on the color combination of the query image, which is followed by the texture based retrieval and finally, based on the entropy of the images, the results are filtered. The proposed system results in retrieving the images from the database which are similar to the query image. Entropy based image retrieval proved to be quite useful in filtering the irrelevant images thereby improving the efficiency of the system. Index Terms—Image Processing, CBIR, Histogram, Wavelets, Quadratic distance, Euclidean distance,
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